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or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high-throughput modeling over
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contributes to a world where differences between children and young people are understood and accepted, strengths are capitalised on, and mental health difficulties are prevented or addressed early in life. We
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the role of autologous fat and muscle cells in breast reconstruction with autologous tissue transfer. The position involves working in parallel with several different cell types, which requires the ability
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controlled crosses between individuals of different ploidies. Sequencing data are already available and include RNA-seq and DNA-seq data for these lines, as well as a reference genome for S. latifolia
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of dense laser plasmas and intense laser interactions with matter using particle-in-cell (PIC), hydrodynamic, and/or Fokker-Planck open and proprietary simulation packages. Investigate and develop different
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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join our research activities focused on the development and long-term durability of SOEC cells, with particular emphasis on operation under technologically relevant conditions. Electrolysis and green
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systems based on massively parallel hardware architectures Combination of programmable logic, tensor processors and general-purpose CPUs for real-time adaption and scheduling services (e.g., AMD Versal
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on competence: contributing to research software development supporting simulations and/or data workflows (HPC/parallel environments), and open/reproducible release of data and analysis scripts under FAIR
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algorithms will be assessed for neurodegeneration mapping in Alzheimer’s disease brain organoids. In parallel, the technology and algorithms will be applied to fish health research, supporting studies on ulcer